Lesson 7: Practice PT - Tell a Data Story

Practice PT | External Tools | Artifact Creation | Project


For this Practice PT students will analyze the data that they have been collecting as a class in order to demonstrate their ability to discover, visualize, and present a trend or pattern they find in the data. Leading up to this lesson, students will have been working in pairs to clean and summarize their data. Students should complete this project individually but can get feedback on their ideas from their data-cleaning partner.

Note: This is NOT the official AP® Performance Task that will be submitted as part of the Advanced Placement exam; it is a practice activity intended to prepare students for some portions of their individual performance at a later time.


Students in this lesson will be telling their own story with a set of data about themselves. The hope is that using personal data will both motivate the exploration of the dataset and provide students with intuitions about the kinds of patterns or trends to explore. This Practice PT reflects many of the practices students will need to use on the actual AP® Performance Tasks, in particular the Explore PT. On that PT, students will need to create an artifact with a computational tool and explain both how it was created and what it is showing.

While students will not be required to create a chart or even necessarily visualize data for the PT, creating a data visualization would make for a strong computational artifact. This activity is designed to provide practice with one way to complete that aspect of the PT. Additionally students should leave this Practice PT familiar with many of the Learning Objectives related to the challenges of manipulating and analyzing data, as they will have now gone through the lifecycle of collecting, cleaning, analyzing, and visualizing data themselves.

AP® is a trademark registered and/or owned by the College Board, which was not involved in the production of, and does not endorse, this curriculum.


Getting Started

Activity (up to 3 days)

Wrap Up


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Students will be able to:

  • Create summaries of a dataset using a pivot table.
  • Manipulate and clean data in order to prepare it for analysis.
  • Explain the process used to create a visualization.
  • Design a visualization that clearly presents a trend, pattern, or relationship within a dataset.
  • Create visualizations of a dataset in order to discover trends and patterns.
  • Draw conclusions from the contents of a data visualization.


Heads Up! Please make a copy of any documents you plan to share with students.

For the Students

Teaching Guide

Getting Started

Introduce the aims and goals of the Practice PT.


Throughout this unit we have been collecting data about ourselves in the hope that we’ll be able to find some interesting trends and patterns in that data. Today we’re going to finally be able to take a close look at the data we’ve collected. Your job will be to use your new skills at cleaning, summarizing, and visualizing data to “tell a story” using the data we collected. We hope that, with so many different perspectives in the class, a lot of interesting stories on the same dataset will emerge.

Activity (up to 3 days)

A proposed schedule of the steps of this project is included in the Teaching Tip as well as more thorough explanations of how to conduct the various stages.

Pacing Suggestion

Below is a suggested timeline for completing the PT entirely in class. It's possible that this could be done in a single day to get most of the work done, with written responses being done for homework.

Day 1

  • Students create individual copies of their data.
  • Students summarize and visualize data, looking for an interesting story to tell.

Day 2

  • Students identify a story in their data.
  • Students design a visualization showing their data story.

Day 3

  • Students complete written responses and submit their Practice PT.

Practice PT: Tell a Data Story


Distribute copies of Practice PT - Tell a Data Story - Rubric rubric and overview to students and review as a class. You may wish to read through the guidelines of the project together.

Alternatively, consider distributing the overview earlier in the unit to provide students an opportunity to preview and prepare.

Below are the steps of the PT that are laid out in the activity guide:

Create Individual Copies of the Data

Students will have been cleaning and summarizing a shared copy of their data thus far. Now they should make separate copies of their data to complete this project. In Google Sheets, one student will need to go to “File” → “Make a copy” In Excel, one student can email the other a copy of their cleaned data

Identify a Story

Students should already have some experience summarizing their data with a pivot table and visualizing it with charts. They should continue to iteratively use these tools to identify an interesting trend, pattern, or relationship within their data. Some good things to remind students:

  • There’s no need to tell a complex story. Simple relationships are still valuable to understand.
  • The absence of a trend or pattern can still be interesting. If the amount of sleep you get doesn’t have a clear impact on mood, that’s interesting to know.

Visualize Your Story

Students should once again refer to the Data Visualization 101 guide for tips on how to make clear visualizations. Their chart will have accompanying explanations, but it should be able to “stand on its own” to communicate the story students have found. Some good things to remind students of:

  • A fancy chart may actually be worse than a simple and clear one.
  • Creating multiple charts is totally appropriate if they will better communicate the story.
  • Experiment with different chart types. The chart type used to discover the story may not actually be the best one for visualizing the story.

Complete Written Responses

In the Practice PT, students will find responses modeled after those that will appear in the actual AP® Performance Tasks.

Wrap Up

Submit Practice PT

Students will need to submit their visualization and written responses. Direct students to check the rubric prior to submission to ensure they have all the necessary components.

Sharing Work

As an optional addition to this project, have students share their findings. The visualizations can be placed around the room for a gallery walk, added to a single shared folder, or presented to the class. This is a good opportunity to see how different groups cleaned and interpreted the same dataset.



Use the provided Practice PT - Tell a Data Story - Rubric rubric, or one of your own creation, to assess students’ submissions.

Standards Alignment

View full course alignment

Computer Science Principles

1.2 - Computing enables people to use creative development processes to create computational artifacts for creative expression or to solve a problem.
1.2.1 - Create a computational artifact for creative expression. [P2]
  • 1.2.1A - A computational artifact is anything created by a human using a computer and can be, but is not limited to, a program, an image, audio, video, a presentation, or a web page file.
  • 1.2.1B - Creating computational artifacts requires understanding and using software tools and services.
  • 1.2.1C - Computing tools and techniques are used to create computational artifacts and can include, but are not limited to, programming IDEs, spreadsheets, 3D printers, or text editors.
  • 1.2.1E - Creative expressions in a computational artifact can reflect personal expressions of ideas or interests.
1.2.2 - Create a computational artifact using computing tools and techniques to solve a problem. [P2]
  • 1.2.2A - Computing tools and techniques can enhance the process of finding a solution to a problem.
  • 1.2.2B - A creative development process for creating computational artifacts can be used to solve problems when traditional or prescribed computing techniques are not effective.
1.2.5 - Analyze the correctness, usability, functionality, and suitability of computational artifacts. [P4]
  • 1.2.5A - The context in which an artifact is used determines the correctness, usability, functionality, and suitability of the artifact.
  • 1.2.5B - A computational artifact may have weaknesses, mistakes, or errors depending on the type of artifact.
  • 1.2.5C - The functionality of a computational artifact may be related to how it is used or perceived.
  • 1.2.5D - The suitability (or appropriateness) of a computational artifact may be related to how it is used or perceived.
3.1 - People use computer programs to process information to gain insight and knowledge.
3.1.3 - Explain the insight and knowledge gained from digitally processed data by using appropriate visualizations, notations, and precise language. [P5]
  • 3.1.3A - Visualization tools and software can communicate information about data.
  • 3.1.3B - Tables, diagrams, and textual displays can be used in communicating insight and knowledge gained from data.
  • 3.1.3C - Summaries of data analyzed computationally can be effective in communicating insight and knowledge gained from digitally represented information.
  • 3.1.3D - Transforming information can be effective in communicating knowledge gained from data.
7.3 - Computing has a global affect -- both beneficial and harmful -- on people and society.
7.3.1 - Analyze the beneficial and harmful effects of computing. [P4]
  • 7.3.1J - Technology enables the collection, use, and exploitation of information about, by, and for individuals, groups, and institutions.

CSTA K-12 Computer Science Standards (2017)

DA - Data & Analysis
  • 3A-DA-11 - Create interactive data visualizations using software tools to help others better understand real-world phenomena.
  • 3B-DA-05 - Use data analysis tools and techniques to identify patterns in data representing complex systems.
  • 3B-DA-06 - Select data collection tools and techniques to generate data sets that support a claim or communicate information.
  • 3B-DA-07 - Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
IC - Impacts of Computing
  • 3A-IC-25 - Test and refine computational artifacts to reduce bias and equity deficits.